15 citations · 30 across the 6 of their papers we have counts for
6 papers
Exploring Beyond Logits: Hierarchical Dynamic Labeling Based on Embeddings for Semi-Supervised Classification
Yanbiao Ma, Licheng Jiao, Fang Liu +3
In semi-supervised learning, methods that rely on confidence learning to generate pseudo-labels have been widely proposed. However, increasing research finds that when faced with n…
Deciphering Spatio-Temporal Graph Forecasting: A Causal Lens and Treatment
Yutong Xia, Yuxuan Liang, Haomin Wen +4
Spatio-Temporal Graph (STG) forecasting is a fundamental task in many real-world applications. Spatio-Temporal Graph Neural Networks have emerged as the most popular method for STG…
Bi-level Multi-objective Evolutionary Learning: A Case Study on Multi-task Graph Neural Topology Search
Chao Wang, Licheng Jiao, Jiaxuan Zhao +4
The construction of machine learning models involves many bi-level multi-objective optimization problems (BL-MOPs), where upper level (UL) candidate solutions must be evaluated via…
Do We Really Need Graph Neural Networks for Traffic Forecasting?
Xu Liu, Yuxuan Liang, Chao Huang +4
Spatio-temporal graph neural networks (STGNN) have become the most popular solution to traffic forecasting. While successful, they rely on the message passing scheme of GNNs to est…
Deep Learning-based Occluded Person Re-identification: A Survey
Yunjie Peng, Saihui Hou, Chunshui Cao +3
Occluded person re-identification (Re-ID) aims at addressing the occlusion problem when retrieving the person of interest across multiple cameras. With the promotion of deep learni…
Correctness of Hierarchical MCS Locks with Timeout
Milind Chabbi, Abdelhalim Amer, Shasha Wen +1
This manuscript serves as a correctness proof of the Hierarchical MCS locks with Timeout (HMCS-T) described in our paper titled "An Efficient Abortable-locking Protocol for Multi-l…